Self-balancing signal relay device based on mckee networking and its assembling and launching method

Abstract

The application relates to a self-balancing signal relay device based on a Mac network station, which comprises an ellipsoidal self-balancing shell, a Mac network module, a power module, a switch module, an antenna and a towing device which are installed on the shell; the Mac network module receives wireless signals through the antenna, adjusts the received data and sends the data; the switch module controls the on-off of the power supply; and the towing device is used for connecting an unmanned device. The storage battery of the power module is located in the middle of the balancing block, the Mac network module is located above the storage battery, and when the towing device is connected with the unmanned device, the switch module is extruded to be powered off; when the towing device is separated, the switch module is bounced to be powered on. The ellipsoidal shell and the balancing block structure ensure that the antenna is automatically kept upward after the device is thrown, the towing device is linked with the switch module, power supply is ensured to be powered off in the state of being connected with the unmanned device and powered on in the state of being separated, power consumption is reduced, and operation convenience is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal relay, in particular to a self-balancing signal relay device based on a Mac network radio station and its assembly and delivery method. BACKGROUND

[0002] At present, most of the related unmanned devices at home and abroad select point-to-point communication connection devices in the selection of wireless communication devices. When working in some complex environments such as building interiors, wireless signals are easily affected by complex terrain or other environmental factors, resulting in a significant reduction in wireless signal communication distance or poor signal transmission quality.

[0003] Although the commonly used cellular mobile network communication module solves the problem of communication distance to a certain extent, it cannot meet the requirement of privacy in some scenarios, and the communication distance problem of closed-loop wireless control in complex environments has not been solved. At the same time, most of the current communication relay modules are hanging or vertical, which need to be installed on the surface of a certain support or have poor structural stability, and it is difficult to maintain balance by themselves. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a self-balancing signal relay device based on a Mac network radio station to solve the above-mentioned defects of the prior art.

[0005] The technical solution adopted by the present application to solve the technical problem is:

[0006] A self-balancing signal relay device based on a Mac network radio station is constructed, which comprises an ellipsoidal self-balancing shell and a Mac network module, a power module, a switch module, an antenna and a towing device mounted on the self-balancing shell.

[0007] The Mac network module is used to receive and adjust signals after receiving wireless signals through the antenna, and to modulate and send data to be sent, the towing device is used to connect unmanned equipment, the power module is used to power the Mac network module, and the switch module is used to control the on-off state of the power module.

[0008] The self-balancing shell comprises an upper shell and a balancing block, the balancing block is formed with a heat dissipation fin assembly on the lower side, the power module comprises a storage battery, a power supply circuit and a charging interface, the storage battery is installed in the middle of the balancing block, and the Mac network module is located above the storage battery.

[0009] Further, when the signal relay device is connected with the unmanned equipment through the towing device, the switch module is extruded to make the power module open circuit, and when the towing device is separated from the unmanned equipment, the switch module is popped up to make the power module pass.

[0010] Further, the balance block is provided with a battery slot for installing a battery and a stud group comprising at least four studs, the Macchiato networking module is fixed on the balance block by connecting with the studs, the upper shell is provided with an arc-shaped groove corresponding to the antenna, a charging slot for fixing the charging interface, and a waterproof cover for closing the charging interface.

[0011] Further, the towing device comprises a lifting ring above the switch module, a lifting hook passing through the lifting ring, a driving member for driving the lifting hook to rotate, and a base plate for installing the driving member, the switch module comprises a press non-self-locking switch and a switch slot provided on the balance block, the press non-self-locking switch is arranged in the switch slot, and the base plate is provided with a pressing block matched with the switch slot, and the pressing block is used for extruding the press non-self-locking switch.

[0012] Further, the heat dissipation fin assembly comprises a plurality of heat dissipation fins, and the length of the heat dissipation fin located at the middle part of the balance block is smaller than that of the heat dissipation fins located at the two sides.

[0013] The application also provides a self-balancing signal relay device based on a Macchiato networking radio station, and the assembly comprises the following steps:

[0014] Step S11: cutting, molding and polishing the rotational molding material to obtain an ellipsoidal self-balancing shell;

[0015] Step S12: fixing the battery in the battery slot of the balance block, leading out the charge-discharge port of the battery through a wire, fixing the Macchiato networking module on the upper part of the balance block, electrically connecting the power supply circuit with the battery, fixing the power supply circuit on one side of the Macchiato networking module, and fixing the antenna on the upper shell through a shielded cable.

[0016] Step S13: electrically connecting the antenna with the Macchiato networking module through a shielded cable, and fixing the antenna on the upper shell.

[0017] Step S14: connecting the switch module to the control port of the power supply circuit through a wire, and fixing the switch module and the towing device in the corresponding slots on the shell through screws, and using a gasket to seal the slots when fixing.

[0018] Step S15: connecting the wire leading out of the charge-discharge port of the battery to the charging interface, installing the charging interface on the charging slot, sealing the charging slot through a gasket, fastening the charging interface through a screw, and closing the charging interface through a waterproof cap.

[0019] Step S16: integrally connecting and fixing the balance block to the bottom of the upper shell through screws.

[0020] The application also provides a method for deploying a self-balancing signal relay device based on a MacLaren networked radio station, which comprises the following steps:

[0021] Step S21: periodically detecting and recording the RSSI value of each channel through the wireless interface of the unmanned device, calculating the ratio of the received signal power to the environmental noise power to obtain the SNR, monitoring and recording the non-target signal events on the channel, calculating the interference level, and counting the active sessions and packet transmission frequency on the channel to obtain the network congestion index;

[0022] Step S22: calculating the score of each channel according to the following formula:

[0023] Channel Score=w1*norm(RSSI)+w2*norm(SNR)-w3*norm(Interference)-w4*norm(Congestion);

[0024] Wherein, w1, w2, w3 and w4 are the weights of RSSI, SNR, interference level and network congestion index, respectively;

[0025] norm is a normalization function, which normalizes each index to the same proportional range;

[0026] Step S23: setting a time period, and selecting the channel with the highest score according to the formula in each period, and comparing the current channel score with the highest score channel at the end of each evaluation period, if the current channel score is lower than the preset percentage threshold of the highest score channel, switching to the channel with the highest score;

[0027] Step S24: when the channel is switched, it is judged whether there is data being transmitted, if there is, the two channels are temporarily used during the switching process.

[0028] Step S25: when the channel score is lower than the minimum score threshold, start timing, and if the signal quality is continuously lower than the threshold for more than 5 periods, the unmanned device deploys the signal relay device.

[0029] Further, in step S22, the weights of RSSI, SNR, interference level and network congestion index need to be dynamically adjusted according to the actual communication effect, and the steps include:

[0030] Step S31: defining a state s, which is a vector of the communication quality indicators of the current channel, specifically s=(RSSI, SNR, Interference, Congestion); defining a behavior a, which represents selecting a target channel from all available channels under a given state s;

[0031] Step S32: Calculate the value of each state-action pair, define the value of each state-action pair as Q value, and the Q value update rule is:

[0032] Q(s,a)←Q(s,a)+α[R(s,a)+γmaxa'Q(s',a')-Q(s,a)]

[0033] Wherein: R(s,a) is the immediate reward function, a is the learning rate, and g is the discount factor;

[0034] Step S33: Define W as the initial weight vector to be optimized, represented as W=[w RSSI ,w SNR ,w Interference ,w Congestion ], and for channel c, the comprehensive score S c is represented as:

[0035] S c = w RSSI *normal ize(RSSI c )+w SNR *normal ize(SNR c )-w Interference *

[0036] normal ize(I c )-w Congestion *normal ize(C c );

[0037] Wherein: RSSI c is the received signal strength indication of channel c; SNR c is the signal-to-noise ratio of channel c; I c is the interference level of channel c; C c is the network congestion level of channel c; normal ize is a normalization function that standardizes data to the range [0,1];

[0038] Step S34: Select the channel with the best communication quality through the objective function, and the objective function is represented as:

[0039] J(W)=∑ c∈C S c ·Q c

[0040] Wherein, C represents the set of all channels, and Q c represents the actual communication quality of channel c;

[0041] Step S35: Calculate the gradient of each weight for the objective function J(W), update the weight vector W using the gradient descent method, and perform weight normalization processing to ensure the sum of the weights is normalized.

[0042] Step S36: Repeat the above steps in each monitoring period to adjust the weights in real time according to the current signal quality.

[0043] Further, in step S35, the gradient of each weight for the objective function J(W) is calculated, which is specifically represented as:

[0044]

[0045] The weight normalization processing ensures that the sum of the weights is 1, which is represented as:

[0046]

[0047] The weight vector W is updated using the gradient descent method, and the update formula is represented as:

[0048]

[0049] Where β is the learning rate, used to control the step size of weight adjustment.

[0050] The beneficial effects of the present application are that the McWiLL radio provides a heartbeat packet containing signal strength, facilitating automatic deployment of signal relay devices by the device, greatly improving the accuracy of signal relay device deployment, and improving the overall signal relay distance.

[0051] The McWiLL module receives wireless signals through the antenna and performs signal adjustment and reception, while modulating and transmitting the data to be sent, providing stable and efficient signal relay functions for the entire device. The combination of the trailer device and the switch module greatly reduces the energy consumption when the device is mounted, without adding additional control circuits, reducing costs and saving overall space, and reducing the overall weight.

[0052] By adopting an ellipsoidal self-balancing shell, the battery is reasonably arranged in the middle of the balancing block, ensuring that the center of gravity of the balancing block is located in the middle of the shell, so that the shell can automatically recover to the position with the antenna pointing upward after being deployed. This design ensures the optimal state of signal reception and transmission, improving the performance and reliability of the signal relay device.

[0053] The balancing block is provided with a heat dissipation fin assembly on the lower side, effectively improving the heat dissipation performance, ensuring the stable operation of the McWiLL module and the battery under high load, and preventing the device from being damaged due to overheating.

[0054] When the towing device is connected with the unmanned device, the switch module is extruded, the power module is disconnected, the signal relay device is ensured not to be accidentally turned on in the non-throwing state, and the electric energy is saved. When the towing device is separated from the unmanned device, the switch module is popped up, the power module is connected, and the device starts to work normally. This design improves the convenience and intelligent level of operation. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the present application will be further described below with reference to the drawings and embodiments. The drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings:

[0056] Figure 1 is an exploded view of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0057] Figure 2 is a structural schematic view of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0058] Figure 3 is a front view of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0059] Figure 4 is a rear view of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0060] Figure 5 is a structure diagram of the towing device of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0061] Figure 6 is a connection schematic view of the towing device of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0062] Figure 7 is an assembly method flow chart of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application;

[0063] Figure 8 is a throwing method flow chart of the self-balancing towable signal relay device based on the Mac network radio station of the preferred embodiment of the present application. DETAILED DESCRIPTION

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, a clear and complete description will be provided below in conjunction with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0065] A preferred embodiment of the present invention is a self-balancing, towable signal repeater based on a McElligott network radio, such as... Figure 1 As shown, see reference Figures 2-6 It includes an ellipsoidal self-balancing housing 1 and a Maxwell networking module 2, a power module 3, a switch module 4, an antenna 5, and a towing device 6 mounted on the self-balancing housing 1.

[0066] The McElliott Networking Module 2 is used to receive wireless signals through the antenna 5, adjust the signal reception, modulate the data to be sent, and send it. The towing device 6 is used to connect unmanned equipment. The power module 3 is used to supply power to the McElliott Networking Module 2. The switch module 4 is used to control the on / off state of the power module 3.

[0067] The self-balancing housing 1 includes an upper housing 11 and a balancing block 12. A heat dissipation fin assembly is formed on the lower side of the balancing block 12. The power module 3 includes a battery 31, a power circuit, and a charging interface 32. The battery 31 is installed in the middle of the balancing block 12, and the Maxwell networking module 2 is located above the battery 31.

[0068] The use of heartbeat packets containing signal strength information in the McElnet network radio facilitates the automatic deployment of signal relay devices, greatly improving the accuracy of signal relay device deployment and increasing the overall signal relay distance.

[0069] By employing an ellipsoidal self-balancing housing, the battery is strategically positioned in the center of the balancing block, ensuring that the center of gravity of the balancing block is located in the middle of the housing. This allows the housing to automatically return to the antenna-facing position after deployment. This design ensures optimal signal reception and transmission, improving the performance and reliability of the signal relay device.

[0070] The lower side of the balance block is provided with a heat dissipation fin assembly. The heat dissipation fin assembly 121 includes multiple heat dissipation fins, which effectively improves heat dissipation performance, ensures stable operation of the MSI networking module and battery under high load, and prevents the equipment from degrading or being damaged due to overheating.

[0071] In this embodiment, the upper and lower shells are made of lightweight and durable materials such as aluminum alloy or ABS engineering plastic, with good strength and impact resistance. The internal key components (battery and mesh networking module) are fixed by elastic support or buffer material to reduce the damage of vibration and impact on the equipment. The charging interface has waterproof sealing function and is designed with protective cover. Subsequent Ethernet interface, USB interface, RS-2 interface, etc. should be set with corresponding protective cover.

[0072] The material of the balance block is high-density metal (such as steel, stainless steel, copper) or lead block, which ensures sufficient center of gravity concentration effect. The battery is located at the center of the bottom of the self-balancing shell, which can ensure the center of gravity of the whole device below, which helps to maintain self-balancing. The middle fin of the heat dissipation fin assembly is shorter, and the two sides are longer to form a ladder shape, which improves the heat dissipation efficiency while maintaining self-balancing. The heat dissipation fin is arranged below the battery to ensure sufficient heat dissipation.

[0073] The towing device adopts hook or buckle mode, which can be quickly connected and separated with unmanned equipment. When the towing device is connected with the switch module, the switch module is pressed when connecting the unmanned equipment to realize power circuit breaking, and the switch module is popped up when separating to realize power circuit.

[0074] The mesh networking module is located at the upper part of the shell and is installed above the balance block, which is fixed by elastic support or buffer material to reduce the influence of vibration. The battery is located in the middle of the balance block to ensure that the center of gravity of the balance block is concentrated in the center position. The power circuit is located near the battery for convenient connection and installation.

[0075] The antenna is mounted on the top of the shell to ensure the optimal state of signal reception and transmission. The antenna is arranged in the arc-shaped groove of the upper shell and is curved, which helps to lower the center of gravity of the overall device and more evenly distribute the weight in the middle of the shell through the reasonable position distribution of the antenna, so that the device maintains a stable self-balancing state. The curvature and shape of the curved antenna are optimized to keep the center of gravity of the device symmetrical, ensuring that the signal relay device can automatically recover to the position with the antenna facing up after the unmanned device is launched. The arc-shaped groove of the upper shell provides a certain protection function for the antenna, avoiding collision and damage of the antenna by external objects during transportation, operation or unmanned device launching. The arc-shaped groove design reduces the exposed area of the antenna, improving the durability and stability of the antenna. The curved antenna is embedded in the arc-shaped groove of the upper shell, effectively reducing the wind resistance of the exposed antenna and reducing the shaking of the device when moving or affected by wind. Reducing shaking helps to maintain the stability of the antenna in receiving and transmitting signals and improves the communication performance of the device. The curved antenna embedded in the arc-shaped groove is precisely designed to ensure that the antenna gain in all directions remains within a proper range to meet the directional requirements of communication. The antenna embedded in the groove not only provides protection and wind resistance, but also makes full use of the space of the shell to provide more space for other internal modules, improving the compactness and practicality of the overall design of the shell. It has waterproof and shockproof functions.

[0076] The shell is assembled by screws or buckles, which is convenient for disassembly and maintenance. All internal modules use standardized interfaces for easy replacement and expansion. The shell is painted or anodized on the outside to improve corrosion resistance.

[0077] As shown in Figure 1 When the signal relay device is connected to the unmanned device through the towing device 6, the switch module 4 is pressed to disconnect the power module 3. When the towing device 6 is disconnected from the unmanned device, the switch module 4 is popped up to connect the power module 3. The switch module is a press switch without self-locking. When the towing device is connected to the unmanned device, the switch module is pressed to disconnect the power module, ensuring that the signal relay device will not be accidentally turned on in the unlaunched state, saving power. When the towing device is disconnected from the unmanned device, the switch module is popped up to connect the power module, and the device starts to work normally. This design improves the convenience and intelligence level of operation.

[0078] As shown in Figures 1-4As shown, the middle of the balance block 12 is provided with a battery slot 13 for installing the battery 31 and a stud set including at least four studs 14, and the Macchiato networking module 2 is fixed on the balance block 12 by connecting with the studs 14. The upper shell 11 is provided with an arc-shaped recess 15 corresponding to the antenna 5, a charging slot 16 for fixing the charging interface 32, and a waterproof sleeve 17 for closing the charging interface 32. The Macchiato networking module receives wireless signals through the antenna and adjusts the signals, and at the same time modulates and transmits the data to be sent, thereby providing stable and efficient signal relay function for the entire device. The combination of the towing device and the switch module greatly reduces the energy consumption of the device when it is mounted, and does not increase the additional control circuit, thereby reducing the cost and saving the overall space and reducing the overall weight.

[0079] As shown in the drawings, Figures 5-6 The towing device 6 includes a lifting ring 61 above the switch module 4, a lifting hook 62 passing through the lifting ring 61, a driving member 63 for driving the lifting hook 62 to rotate, and a base plate 64 for installing the driving member 63. The switch module 4 includes a press non-latching switch 41 and a switch slot 42 provided on the balance block 12. The press non-latching switch 41 is arranged in the switch slot 42. When the relay device is prevented from being on the horizontal ground and is in a stable state, the lifting ring and the switch are on the same vertical line. The base plate 64 is provided with a pressing block 65 matched with the switch slot 42, and the pressing block 65 is used to press the press non-latching switch 41. The base plate is fixed on the unmanned device. When it is necessary to connect the signal relay device with the unmanned device, the driving member 63 is started, and the driving member controls the lifting hook 62 to rotate and is fixed on the unmanned device through the lifting ring 61. At this time, the pressing block 65 on the base plate 64 presses the press non-latching switch 41 in the switch module 4, causing the switch to be off, thereby cutting off the power supply of the power module 3, ensuring that the device does not consume power during the connection process. When the signal relay device needs to be removed from the unmanned device, the driving member 63 is started again to release the lifting hook 62 from the lifting ring 61. With the release of the lifting hook, the pressing block 65 on the base plate 64 moves away and releases the press non-latching switch 41. The switch returns to the on state due to the spring rebound effect, and the power module 3 is powered on, and the signal relay device returns to the working state.

[0080] When the hook is linked with the ring, the rotation of the hook can be automatically controlled by the driving member to realize the quick connection and release of the towing device and the unmanned equipment. Through the interaction of the pressing block on the base plate and the switch module, the on-off state of the switch is automatically controlled to improve the convenience and safety of operation. The designed ring and hook ensure the stable connection of the towing device and the unmanned equipment, reducing accidental disconnection caused by vibration or movement. At the same time, the switch module realizes the switching of the power supply through physical pressing, avoiding complex electronic control and improving the reliability of the system. When the unmanned equipment is connected, the power supply is automatically disconnected to avoid consuming power when not needed, thereby prolonging the service life of the battery and reducing energy consumption. Through the automatic control of the hook rotation by the driving member, the user can complete the connection and disconnection without manual operation, which greatly improves the operation efficiency and response speed. Through this design, the signal relay device can automatically control the switch of the power supply when connecting and disconnecting the unmanned equipment, improving the convenience and safety of operation, and also protecting the service life of the power supply module.

[0081] As shown in Figures 1-4 The length of the middle heat dissipation fins is less than that of the fins on both sides of the balance block 12. The center of gravity is stable and the self-balancing ability is improved: the middle heat dissipation fins are shorter, so that the center of gravity of the balance block is more concentrated in the middle of the shell, thereby helping to improve the self-balancing ability of the device and ensuring that the device automatically recovers to the position with the antenna upward after being released, maintaining the best signal receiving and sending state. The longer fins on both sides ensure that the mass of the device is evenly distributed, effectively preventing tilting and rolling, and helping to maintain the stability of the device. The shorter middle fins concentrate the mass, further improving the self-balancing performance in cooperation with the design of the balance block. The design of heat dissipation fins of different lengths makes the lower side of the device have a stepped heat dissipation structure, which helps air flow and speeds up heat dissipation. The longer fins on both sides are responsible for main heat dissipation, and the shorter fins in the middle ensure compact structure while providing auxiliary heat dissipation function. The shorter middle fins provide more space for the installation and layout of internal components, allowing more flexible installation of batteries and mesh networking modules, reducing interference, and improving the rationality and compactness of the overall design of the device.

[0082] The present application also provides an embodiment of a self-balancing signal relay device based on a mesh networking station, as shown in Figure 7 The assembly includes the following steps:

[0083] Step S11: cutting, molding and polishing the rotational molding material to obtain an ellipsoidal self-balancing shell 1;

[0084] Step S12: fixing the battery 31 in the battery groove of the balance block 12, leading out the charge and discharge port of the battery 31 through the wire, fixing the mesh networking module 2 on the upper part of the balance block 12, electrically connecting the power supply circuit with the battery 31, and fixing the power supply circuit on one side of the mesh networking module 2;

[0085] Step S13: The antenna 5 is electrically connected to the Meixi networking module 2 through a shielded cable, and the antenna 5 is fixed on the upper shell 11;

[0086] Step S14: The switch module 4 is connected to the control port of the power supply circuit through a wire, and the switch module 4 and the trailer device 6 are fixed in the corresponding slot on the shell by screws, and the slot is sealed by using a gasket with the screw;

[0087] Step S15: The wire leading out of the charge-discharge port of the battery 31 is connected to the charging interface 32, and the charging interface 32 is installed on the charging groove 16. After the charging groove 16 is sealed by a gasket, the charging interface 32 is fastened by a screw, and the charging interface 32 is closed by a waterproof sleeve 17. The shell cooperates with the gasket to make the signal relay device of the application have an IP67 protection level, dustproof and waterproof.

[0088] Step S16: The balance block 12 is integrally connected and fixed at the bottom of the upper shell 11 by screws.

[0089] The ellipsoidal self-balancing shell made of rotational molding material has lighter weight and higher strength, ensuring the protection ability and self-balancing performance of the shell. The design and fixed position of the balance block ensure that the shell can automatically maintain the position of the antenna pointing upward after being thrown, realizing self-balancing. The battery is fixed in the battery groove of the balance block, ensuring the concentration of the center of gravity of the balance block. The Meixi networking module is installed above the battery through a stud, ensuring effective heat dissipation and stable operation of the signal transmission module.

[0090] The power supply circuit is electrically connected to the battery and fixed on one side of the Meixi networking module, realizing compact layout, reducing cable interference, and improving the reliability of the system. The antenna is connected to the Meixi networking module through a shielded cable and fixed in the arc-shaped groove of the upper shell, improving the wind resistance performance and signal performance of the device, and protecting the antenna through the groove structure to reduce damage.

[0091] The non-self-locking switch is connected to the control port of the power supply circuit and linked with the trailer device. When the trailer device is connected to the unmanned device, it is powered off, and when the trailer device is disconnected, it is powered on, ensuring the automatic control of the power switch and improving the operation convenience of the device.

[0092] Modular design, reasonable arrangement of the antenna and IP67 protection level ensure the signal transmission performance of the device and the reliability of the whole device. Each module is independently installed, the structure is compact, and the whole device has high maintainability and expandability.

[0093] A self-balancing signal relay device based on Meixi networking radio station is shown in Figure 8 The method comprises the following steps:

[0094] Step S21: Periodically detect and record the RSSI value of each channel through the wireless interface of the unmanned device, calculate the ratio of received signal power to environmental noise power to obtain SNR, monitor and record non-target signal events on the channel, calculate the interference level, and count the active sessions and packet transmission frequency on the channel to obtain network congestion indicators;

[0095] Step S22: Calculate the score of each channel according to the following formula:

[0096] Channel Score = w1*norm(RSSI) + w2*norm(SNR) - w3*norm(Interference) - w4*norm(Congestion);

[0097] Where w1, w2, w3 and w4 are the weights of RSSI, SNR, interference level and network congestion indicators, respectively;

[0098] norm is a normalization function that normalizes each indicator to the same scale range; according to different application requirements and interference environment adjustment strategies, the communication effect is improved. Support user-defined weight configuration to improve the applicability and flexibility of the scheme.

[0099] Step S23: Set a time period, and select the channel with the highest score according to the formula in each period. At the end of each evaluation period, compare the current channel score with the highest score channel. If the current channel score is lower than the preset percentage threshold of the highest score channel, switch to the channel with the highest score;

[0100] Step S24: When switching channels, determine whether there is data being transmitted. If so, temporarily use both channels during the switching process; this can ensure communication continuity, reduce data loss and network interruption, and improve user experience. Dynamic channel switching ensures the flexibility of communication and ensures that the optimal channel is always used.

[0101] Step S25: When the channel score is lower than the minimum score threshold, start timing. If the signal quality continues to be lower than the threshold for more than 5 periods, the unmanned device will deploy a signal relay device. This improves the redundancy and reliability of the communication network and ensures that the signal relay device is deployed in a timely manner. By continuously monitoring, the risk of signal degradation is identified and addressed in a timely manner, improving network robustness.

[0102] The self-balancing design of the signal relay device ensures that the device can automatically keep the antenna pointing upwards after deployment and relay signals through the best channel. This improves the efficiency and effectiveness of device deployment and ensures that the signal relay device operates in the optimal state. After deployment, it automatically stabilizes, improving signal reception and transmission quality.

[0103] The unmanned device can determine and automatically deploy the signal relay device according to the signal quality deterioration condition, reduce human intervention, and improve deployment efficiency. The error and interference of human operation are reduced, and the deployment accuracy of the signal relay device is improved. The deployment efficiency is improved, and the communication network interruption time is reduced.

[0104] Through the above method, the self-balancing signal relay device based on the McWilliams networking radio station can automatically select the best channel, realize dynamic channel switching, maintain communication continuity, and ensure that the standby signal relay device is automatically deployed in the case of continuous deterioration of channel quality. This method effectively improves the communication quality and network stability of the signal relay device, and improves the adaptability, flexibility and reliability of the communication network.

[0105] In step S22 in the embodiment, the weights of RSSI, SNR, interference level and network congestion index need to be dynamically adjusted according to the actual communication effect, and the steps include:

[0106] Step S31: define a state s, which is represented as a vector of communication quality indicators of the current channel, specifically s=(RSSI, SNR, Interference, Congestion); define a behavior a, which represents selecting a target channel from all available channels under a given state s;

[0107] Step S32: calculate the value of each state-action pair, and define the value of each state-action pair as Q value. The Q value update rule is:

[0108] Q(s,a)←Q(s,a)+α[R(s,a)+γmaxa'Q(s',a')-Q(s,a)]

[0109] Where: R(s,a) is the reward function, a is the learning rate, and g is the discount factor;

[0110] Specifically,

[0111] Q(s,a): the value estimate of action a in state s, that is, the expected total reward value that can be obtained by executing action a in state s and following the optimal strategy.

[0112] R(s,a): the immediate reward when action a is executed in state s.

[0113] a: learning rate, controls the update step size, and the range is between (0, 1).

[0114] g: discount factor, controls the discounting effect of future rewards, and the range is between (0, 1).

[0115] s': the new state reached after executing action a.

[0116] a': Actions under state s'.

[0117] maxa'Q(s',a'): The maximum value estimate that can be obtained by choosing action a' under the new state s'.

[0118] The reward function R(s,a) directly measures the immediate reward obtained after performing action a in state s, selecting the action that best benefits long-term gains in a specific state. For a specific state s and action a, the reward function can be expressed as:

[0119] R(s,a)=w RSSI *normalize(RSSI)+w SNR *normalize(SNR)-W Interference *normalize(Interference)-W Congestion *normalize(Congestion)

[0120] Among them: w RSSI ,w SNR W Interference W Congestion Weights for each metric.

[0121] normalize is a normalization function that standardizes each metric to the range [0,1].

[0122] Using the Q-value (the value of a state-behavior pair) as the basis for channel selection, the reward function (R) is closely integrated with the actual communication effect. The Q-value is updated in real time according to the formula, ensuring that the optimal channel is always selected under a given state. Utilizing reinforcement learning algorithms and Q-value update rules, the channel selection strategy can dynamically adapt to changes in the channel environment and accurately select the target channel. This ensures accurate prediction of the optimal target channel under each state, improving the accuracy of channel selection and reducing interruptions and interference in signal transmission.

[0123] Step S33: Define W as the initial weight vector to be optimized, expressed as W = [w RSSI ,w SNR ,w Interference ,w Congestion For channel c, its overall score S c Represented as:

[0124] S c =w RSSI *normalize(RSSI) c )+w SNR *normalize(SNR) c )-w Interference *

[0125] normalize(I c ) - w Congestion * normalize(C c ) ;

[0126] wherein: RSSI c is the received signal strength indication of channel c; SNR c is the signal to noise ratio of channel c; I c is the interference level of channel c; C c is the network congestion level of channel c; normalize is a normalization function that normalizes data to the range [0, 1];

[0127] After the initial weight vector, the signal quality data of each channel is normalized, i.e.:

[0128] RSSI: normalized from -100 dBm to -30 dBm to [0, 1]

[0129] normalize(RSSI) = [RSSI - (-100)] / [-30 - (-100)]

[0130] SNR: normalized from 0 dB to 40 dB to [0, 1]

[0131] normalize(SNR) = [SNR - 0] / [40 - 0]

[0132] Interference: normalized from 0 to 100 to [0, 1]

[0133] normalize(Interference) = [Interference - 0] / [100 - 0]

[0134] Network congestion: normalized from 0 to 100 to [0, 1].

[0135] normalize(Congestion) = [Congestion - 0] / [100 - 0]

[0136] Step S34: Select the channel with the best communication quality through the objective function, which is expressed as:

[0137] J(W) = ∑ c∈C S c · Q c

[0138] wherein C represents the set of all channels, Q c represents the actual communication quality of channel c;

[0139] The objective function J(W) combines the channel comprehensive score Sc and the actual communication quality Qc to select the channel with the best communication quality by optimizing the objective function. The objective function reasonably considers the quality indicators of each channel to ensure that the selection strategy is scientific and reliable. The objective function associates the channel comprehensive score with the actual communication quality to ensure that the channel selection strategy is closer to the actual communication effect. The use of the objective function optimization strategy makes the channel selection more scientific, reasonably balances the importance of each quality indicator, and improves the effectiveness of channel selection.

[0140] Step S35: Calculate the gradient of each weight for the objective function J(W), update the weight vector W using the gradient descent method, and perform weight normalization processing to ensure that the sum of the weights is normalized.

[0141] The gradient of each weight for the objective function J(W) is calculated, and the weight vector W is optimized using the gradient descent method. The gradient descent method is executed in each cycle to ensure that the weights are dynamically adjusted based on the current actual communication quality, and the weight vector normalization processing ensures that the relative importance between indicators is reasonable. The gradient descent method continuously optimizes the weights, allowing the channel selection strategy to adapt to changes in the network environment and improving the flexibility of channel selection. Weight normalization ensures that the total weight of each indicator in the channel score is reasonably distributed, preventing excessive influence of a single indicator on the result.

[0142] Step S36: Repeat the above steps in each monitoring period to adjust the weights in real time based on the current signal quality.

[0143] In step S35, the gradient of each weight for the objective function J(W) is calculated, which is specifically represented as:

[0144]

[0145] The weight normalization processing ensures that the sum of the weights is 1, which is represented as:

[0146]

[0147] The weight vector W is updated using the gradient descent method, and the update formula is represented as:

[0148]

[0149] where β is the learning rate, which is used to control the step size of weight adjustment.

[0150] The application utilizes a reinforcement learning algorithm to dynamically adjust the weight of each channel evaluation index (RSSI, SNR, interference level, network congestion) in real time according to actual communication effect. In different environments, the relative importance of each index to channel selection is different, and dynamic adjustment of the weight enables the channel selection strategy to flexibly respond to changes in the channel environment. Real-time adjustment of the weight ensures that the best channel can always be selected in different environments, improving the signal transmission stability and adaptability of the signal relay device. Through adaptive adjustment of the weight, the channel selection strategy can respond in a timely manner to changes such as new signal interference, network congestion, etc., improving communication quality. The target function design and gradient descent optimization weight strategy make channel selection more scientific, reasonably integrate various channel quality indexes, and improve network robustness. Unmanned equipment and signal relay devices are deployed in linkage, improving network redundancy and automation level, and reducing human intervention and operation errors.

[0151] It should be understood that the application is not limited to the above best mode of implementation, and anyone can derive other various forms of products under the inspiration of the application, but regardless of any changes in shape or structure, any technical solution with the same or similar technical solutions as this application falls within the protection scope of the application.

Claims

1. A self-balancing signal repeater based on a McElligott network radio, characterized in that, It includes an ellipsoidal self-balancing housing (1) and a McElliott networking module (2), a power module (3), a switch module (4), an antenna (5), and a towing device (6) mounted on the self-balancing housing (1); The McElliott Network Module (2) is used to receive wireless signals through the antenna (5), adjust the signal reception, modulate the data to be sent, and send it. The towing device (6) is used to connect unmanned equipment. The power module (3) is used to supply power to the McElliott Network Module (2). The switch module (4) is used to control the on / off state of the power module (3). The self-balancing housing (1) includes an upper housing (11) and a balancing block (12). A heat dissipation fin assembly (121) is formed on the lower side of the balancing block (12). The power module (3) includes a battery (31), a power circuit and a charging interface (32). The battery (31) is installed in the middle of the balancing block (12). The Maxwell networking module (2) is located above the battery (31). The delivery method includes the following steps: Step S21: Periodically detect and record the RSSI value of each channel through the wireless interface of the unmanned equipment, calculate the ratio of received signal power to ambient noise power to obtain SNR, monitor and record non-target signal events on the channel, calculate the interference level, and count the active sessions and data packet transmission frequency on the channel to obtain network congestion indicators. Step S22: Calculate the score for each channel according to the following formula: Channel Score=w1*norm(RSSI)+w2*norm(SNR)-w3*norm(Interference)-w4*norm(Congestion); Among them, w1, w2, w3 and w4 are the weights of RSSI, SNR, interference level and network congestion index, respectively; norm is a normalization function used to standardize each indicator to the same proportional range; The weights of RSSI, SNR, interference level, and network congestion indicators need to be dynamically adjusted based on actual communication performance. The steps include: Step S31: Define a state s, which is a vector of communication quality indicators for the current channel, specifically s = (RSSI, SNR, Interference, Congestion); define a behavior a, which represents selecting a target channel from all available channels given state s. Step S32: Calculate the value of each state-action pair, and define the value of each state-action pair as the Q-value. The Q-value update rule is as follows: Q(s,a)←Q(s,a)+α[R(s,a)+γmaxa'Q(s',a')-Q(s,a)] Where R(s,a) is the immediate reward function, α is the learning rate, and γ is the discount factor; Step S33: Define W as the initial weight vector to be optimized, expressed as W = [w RSSI ,w SNR ,w Interference ,w Congestion For channel c, its overall score S c Represented as: S c =w RSSI *normalize(RSSI c )+w SNR *normalize(SNR c )-w Interference *normalize(I c )-w Congestion *normalize(C c ); Among them: RSSI c For channel c, the received signal strength indicator; SNR c For channel c, the signal-to-noise ratio; I c The interference level for channel C; C c The network congestion level for channel c; normalize is a normalization function that normalizes the data to the range [0,1]. Step S34: Select the channel with the best communication quality using an objective function, which is expressed as: J(W)=∑ c∈C S c ·Q c Where C represents the set of all channels, and Qc represents the actual communication quality of channel c; Step S35: Calculate the gradient of each weight for the objective function J(W), update the weight vector W using gradient descent, and perform weight normalization to ensure that the sum of weights is normalized; Step S36: Repeat the above steps in each monitoring cycle and adjust the weights in real time according to the current signal quality; Step S23: Set a time period. In each period, select the channel with the highest score according to the formula. At the end of each evaluation period, compare the current channel score with the highest score channel. If the current channel score is lower than the preset percentage threshold of the highest score channel, switch to the highest score channel. Step S24: When switching channels, determine whether there is data being transmitted. If so, temporarily use two channels during the switching process. Step S25: When the channel score is lower than the minimum score threshold, start timing. If the signal quality remains below the threshold for more than 5 cycles, the unmanned equipment will deploy the signal relay device.

2. The self-balancing signal relay device based on McElligott network radio as described in claim 1, characterized in that, When the signal relay device is connected to the unmanned equipment via the towing device (6), the switch module (4) is squeezed to disconnect the power module (3). When the signal relay device is detached from the unmanned equipment, the switch module (4) pops up to restore the power module (3).

3. The self-balancing signal relay device based on McElligott network radio as described in claim 1, characterized in that, The balance block (12) is provided with a stud assembly and a battery slot (13) for installing the battery (31) in the middle. The stud assembly includes at least four studs (14). The McLaren networking module (2) is fixed on the balance block (12) by connecting to the studs (14). The upper housing (11) is provided with an arc-shaped groove (15) corresponding to the antenna (5), a charging slot (16) for fixing the charging interface (32), and a waterproof sleeve (17) for sealing the charging interface (32).

4. The self-balancing signal relay device based on McElligott network radio according to claim 3, characterized in that, The towing device (6) includes a lifting ring (61) located above the switch module (4), a hook (62) passing through the lifting ring (61), a drive member (63) for driving the hook (62) to rotate, and a base plate (64) for mounting the drive member (63). The switch module (4) includes a press-to-lock switch (41) and a switch slot (42) provided on the balance block (12). The press-to-lock switch (41) is provided in the switch slot (42). The base plate (64) is provided with a pressing block (65) that matches the switch slot (42). The pressing block (65) is used to press the press-to-lock switch (41).

5. The self-balancing signal relay device based on McElligott network radio as described in claim 1, characterized in that, The heat dissipation fin assembly (121) includes multiple heat dissipation fins, with the heat dissipation fins located in the middle of the balance block (12) having a shorter length than the heat dissipation fins on both sides.

6. A self-balancing signal repeater based on a McElligott network radio as described in any one of claims 1-5, the assembly of which includes the following steps: Step S11: Cut, shape and polish the rotational molding material to obtain an ellipsoidal self-balancing shell (1); Step S12: Fix the battery (31) in the battery slot of the balance block (12), and lead out the charging and discharging port of the battery (31) through the wire, fix the Magnet module (2) on the upper part of the balance block (12), and then connect the power circuit to the battery (31). Step S13: Connect the antenna (5) to the McElnet networking module (2) via a shielded cable and fix the antenna (5) on the upper housing (11); Step S14: Connect the switch module (4) to the control port of the power circuit through the wire, and then fix the switch module (4) and the towing device (6) in the corresponding slots set on the housing with screws. When fixing, use washers to seal the slots with screws. Step S15: Connect the wires leading out from the charging and discharging port of the battery (31) to the charging interface (32), install the charging interface (32) onto the charging slot (16), seal the charging slot (16) with a gasket, tighten the charging interface (32) with screws, and seal the charging interface (32) with a waterproof sleeve (17). Step S16: Fix the balance block (12) to the bottom of the upper housing (11) by screws.

7. A self-balancing signal relay device based on a McElligott network radio as described in any one of claims 1-5, wherein the deployment method comprises the following steps: Step S21: Periodically detect and record the RSSI value of each channel through the wireless interface of the unmanned equipment, calculate the ratio of received signal power to ambient noise power to obtain SNR, monitor and record non-target signal events on the channel, calculate the interference level, and count the active sessions and data packet transmission frequency on the channel to obtain network congestion indicators. Step S22: Calculate the score for each channel according to the following formula: Channel Score=w1*norm(RSSI)+w2*norm(SNR)-w3*norm(Interference)-w4*norm(Congestion); Among them, w1, w2, w3 and w4 are the weights of RSSI, SNR, interference level and network congestion index, respectively; norm is a normalization function used to standardize each indicator to the same proportional range; Step S23: Set a time period. In each period, select the channel with the highest score according to the formula. At the end of each evaluation period, compare the current channel score with the highest score channel. If the current channel score is lower than the preset percentage threshold of the highest score channel, switch to the highest score channel. Step S24: When switching channels, determine whether there is data being transmitted. If so, temporarily use two channels during the switching process. Step S25: When the channel score is lower than the minimum score threshold, start timing. If the signal quality remains below the threshold for more than 5 cycles, the unmanned equipment will deploy the signal relay device. In step S22, the weights of RSSI, SNR, interference level, and network congestion indicators need to be dynamically adjusted based on the actual communication performance. The steps include: Step S31: Define a state s, which is a vector of communication quality indicators for the current channel, specifically s = (RSSI, SNR, Interference, Congestion); define a behavior a, which represents selecting a target channel from all available channels given state s. Step S32: Calculate the value of each state-action pair, and define the value of each state-action pair as the Q-value. The Q-value update rule is as follows: Q(s,a)←Q(s,a)+α[R(s,a)+γmaxa'Q(s',a')-Q(s,a)] Where R(s,a) is the immediate reward function, α is the learning rate, and γ is the discount factor; Step S33: Define W as the initial weight vector to be optimized, expressed as W = [w RSSI ,w SNR ,w Interference ,w Congestion For channel c, its overall score S c Represented as: S c =w RSSI *normalize(RSSI c )+w SNR *normalize(SNR c )-w Interference *normalize(I c )-w Congestion *normalize(C c ); Among them: RSSI c For channel c, the received signal strength indicator; SNR c For channel c, the signal-to-noise ratio; I c The interference level for channel C; C c The network congestion level for channel c; normalize is a normalization function that normalizes the data to the range [0,1]. Step S34: Select the channel with the best communication quality using an objective function, which is expressed as: J(W)=∑ c∈C S c ·Q c Where C represents the set of all channels, Q c This indicates the actual communication quality of channel c; Step S35: Calculate the gradient of each weight for the objective function J(W), update the weight vector W using gradient descent, and perform weight normalization to ensure that the sum of weights is normalized; Step S36: Repeat the above steps in each monitoring cycle and adjust the weights in real time according to the current signal quality; In step S35, the gradient of each weight is calculated for the objective function J(W), specifically expressed as: Weight normalization ensures that the sum of the weights is 1, expressed as: The weight vector W is updated using gradient descent, and the update formula is expressed as follows: Where β is the learning rate, used to control the step size of weight adjustment.

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